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Mesh Topology Identification for Mass-Spring Models

G. Bianchi, M. Harders and G. Székely
Medical Image Computing and Computer-Assisted Intervention MICCAI 2003
Montreal, Canada, November 2003

Abstract

In surgical simulations, the two most popular approaches to model soft tissues are Finite Element Method (FEM) and Mass-Spring System (MSS). Main advantages of FEM are accuracy and realism. Furthermore, the model allows the direct integration of experimentally obtained biomechanical tissue parameters. However, computation times remain high, limiting real-time application of the method. In contrast to this, the main advantage of MSS is low computational complexity and simple implementation. These factors make the latter method highly attractive for virtual reality based surgical simulators. However, the specification of system parameters for a MSS (masses, spring constants, mesh topology) is not straightforward and remains a major difficulty of the approach. In this paper, we propose a solution to this problem based on evolutionary algorithms - our current focus being the determination of mesh topology. We use reference models to obtain the topology of a MSS. First results demonstrate, that the exact recovery of isotropic and anisotropic reference mesh configurations is possible.


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@InProceedings{eth_biwi_00274,
  author = {G. Bianchi and M. Harders and G. Székely},
  title = {Mesh Topology Identification for Mass-Spring Models},
  booktitle = {Medical Image Computing and Computer-Assisted Intervention MICCAI 2003},
  year = {2003},
  month = {November},
  pages = {50-58},
  volume = {1},
  keywords = {Mass-Spring, genetic algorithm, topology, parameter identification}
}